Job Title: Software/AI Engineer
Location: Remote
Job Type: 6 months contract
Job Summary
We are looking for a strong experience in cloud-based data and AI engineering, Generative AI, Large Language Models (LLMs), RAG architectures, and AI application development.
The ideal candidate will have practical experience building and deploying AI/GenAI solutions on AWS or Google Cloud Platform, with Azure experience being a plus. The candidate should be comfortable working with LLMs, RAG architectures, AI frameworks, data pipelines, APIs, and production-grade cloud applications.
This is a hands-on engineering role requiring strong programming skills and the ability to design, develop, integrate, test, troubleshoot, and deploy AI-powered solutions.
Key Responsibilities
Design, develop, and deploy cloud-based data and AI solutions using AWS or Google Cloud Platform.
Build scalable and production-ready applications using Python and other modern programming languages.
Develop and integrate Generative AI and LLM-powered applications.
Work with commercial and open-source LLMs such as:
OpenAI / GPT
Meta Llama
Google Gemini
Other open-source LLMs
Build and implement Retrieval-Augmented Generation (RAG) solutions.
Design RAG pipelines including document ingestion, preprocessing, chunking, embeddings, retrieval, reranking, context management, and response generation.
Work with LangChain, LlamaIndex, LangGraph, and similar GenAI frameworks.
Develop AI agents and graph-based AI workflows where applicable.
Build integrations between LLMs, enterprise applications, APIs, databases, data platforms, and cloud services.
Develop data ingestion and transformation pipelines supporting AI/ML and GenAI applications.
Work with both structured and unstructured data.
Implement vector search, embeddings, and vector database solutions.
Build APIs and backend services to expose AI capabilities to enterprise applications.
Implement monitoring, logging, testing, evaluation, and observability for AI/LLM applications.
Optimize AI applications for performance, scalability, reliability, security, and cost.
Troubleshoot production issues and continuously improve AI and data engineering solutions.
Collaborate with architects, data engineers, software engineers, product teams, and business stakeholders to translate requirements into technical solutions.
Required Skills & Experience
Programming Languages
Strong hands-on programming experience with one or more of the following:
Python strongly preferred for AI/GenAI and data engineering
C# / .NET
Java
JavaScript
TypeScript
Candidates should be able to write production-quality code and should have strong software engineering fundamentals.
Cloud & Engineering
Strong hands-on experience with AWS or Google Cloud Platform.
Experience developing and deploying applications/services in a cloud environment.
Experience with cloud-native architectures and services.
Azure experience is a plus.
Experience developing APIs and backend services.
Experience with databases and distributed/cloud-based systems.
Understanding of containers, serverless technologies, CI/CD, and DevOps practices is preferred.
Generative AI / LLM
Strong practical experience with Generative AI and Large Language Models, including one or more of:
OpenAI / GPT models
Meta Llama
Google Gemini
Open-source LLMs
LLM APIs and model integration
Prompt engineering
Embeddings
Vector search
Model evaluation and optimization
RAG & AI Application Development
Hands-on experience building RAG-based applications, including:
Document ingestion
Data preprocessing and chunking
Embeddings
Vector databases / vector search
Semantic retrieval
Context construction
Prompt orchestration
Response generation
RAG evaluation and optimization
Experience with:
LangChain
LlamaIndex
LangGraph
Other equivalent GenAI frameworks